Technology has always played a role in inspiring musicians in new and creative ways. The guitar amp gave rock musicians a new palette of sounds to play with in the form of feedback and distortion. And the sounds generated by synths helped shape the sound of electronic music. But what about new technologies like machine learning models and algorithms? How might they play a role in creating new tools and possibilities for a musician’s creative process? Magenta, a research project within Google, is currently exploring answers to these questions.
Building upon past research in the field of machine learning and music, last year Magenta released NSynth (Neural Synthesizer). It’s a machine learning algorithm that uses deep neural networks to learn the characteristics of sounds, and then create a completely new sound based on these characteristics. Rather than combining or blending the sounds, NSynth synthesizes an entirely new sound using the acoustic qualities of the original sounds—so you could get a sound that’s part flute and part sitar all at once.
Since then, Magenta has continued to experiment with different musical interfaces and tools to make the algorithm more easily accessible and playable. As part of this exploration, Google Creative Lab and Magenta collaborated to create NSynth Super. It’s an open source experimental instrument which gives musicians the ability to explore new sounds generated with the NSynth algorithm.